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Empirical wavelet analysis of tail and memory properties of LARCH and FIGARCH models

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  • Agnieszka Jach

    ()

  • Piotr Kokoszka

    ()

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    Abstract

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    File URL: http://hdl.handle.net/10.1007/s00180-009-0168-6
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    Bibliographic Info

    Article provided by Springer in its journal Computational Statistics.

    Volume (Year): 25 (2010)
    Issue (Month): 1 (March)
    Pages: 163-182

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    Handle: RePEc:spr:compst:v:25:y:2010:i:1:p:163-182

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    Related research

    Keywords: Heavy tails; Long memory; Volatility; Wavelets; 62M10; 42C40;

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    1. Michel Beine & Sebastien Laurent & Christelle Lecourt, 2002. "Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 12(8), pages 589-600.
    2. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 177-210.
    3. GIRAITIS, Liudas & KOKOSZKA, Piotr & LEIPUS, Remigijus & TEYSSIÈRE, Gilles, . "Rescaled variance and related tests for long memory in volatility and levels," CORE Discussion Papers RP -1594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Basrak, Bojan & Davis, Richard A. & Mikosch, Thomas, 2002. "Regular variation of GARCH processes," Stochastic Processes and their Applications, Elsevier, vol. 99(1), pages 95-115, May.
    5. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
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